Quantitative methods include statistical
Methods can be divided into three types:
1. Trend projection method
2. Barometer method.
3. Econometric method.
The meaningmatic method can also be divided into two types:
(i) regress method
(ii) Method together
First we know what statistical method is?

statistical methods
Statistical methods are considered to be a better technology of demand assessment. The statistical method usually uses historical (time-series) and cross-section data to predict long-term demand.
Statistical methods are better for the following reasons:
1. Estimates are relatively more reliable.
2. Estimate includes low cost.
3. The element of personality in statistical methods is minimum.
4. The method of estimation is scientific, because it is based on theoretical relationship between dependent and independent variable.
A firm can predict sale by fitting the trends in the time series. This can be done either by the graphic method or by fitting the trend line by the algebra equation. Linear trend. The linear trend equation is as follows: YS = A + Bx
2. Barometer method – the barometer method is also known as the leading indicator forecast. Three types of indicators have been identified by the United States National Economic Research Bureau, they are-
Leading indicators, cooperative indicators and backward indicators. Leading series have indicators that move upwards to another series. Some examples of this series are:
(i) index of prices of materials,
(ii) new building permit,
(iii) New orders for durable items
The coincidence series are those that run up or down along with the level of economic activity. Some examples of the coincidence series are:
(i) sales recorded by manufacturing, trade and retail areas,
(ii) Number of employees in non-agriculture sector,
(iii) rate of unemployment.
The legging series include indicators that follow the change after a while interval. Some examples are:
(i) outstanding loan,
(ii) labor cost per unit of manufactured production.
(iii) lending rate for short term loan.
3. The Economic Method – The Economic Method combines statistical devices with economic principles to predict economic variables and to forecast the desired economic variables. The forecast made through economical methods is much more realistic than other methods. Therefore they are more widely used to forecast product demand for a product group and an overall economy.
A econometric model single equation can be a regression model or it can involve a system of equation simultaneously.
Here is briefly description of the meaningful method:
(i) the transit method,
(ii) simultaneous equation method
(i) Immigration method – this is a very useful method of forecasting. The regression analysis explains the functional relationship between independent variables and dependent variables. In this method, factors affecting the demand of the respective object are determined to estimate the demand of an object. Then, using the regression technology, an attempt to predict the demand function of the object in question. In the regimen analysis of the prediction of the object’s demand, dependent variable is demand. Independent variable can be one. In case of some items, while for other items it may be more than two. Therefore, any single can use simple or multiple regress to predict demand.
(ii) Together equation method – A single equation technology of demand forecasting contains a single equation. In contrast, the equation model of the forecast together includes an estimate of several equations. The regression technology considers only one way of cause-reason i.e. only independent variables cause variations in dependent variables, not the contrary, which is an unrealistic notion, on the other hand, the forecast through the meaningmatic model of the equation together enables the prediction to keep in mind the dependent and independent, the conversation together between the variables. The first step in this technology is to develop a whole model and specify the behavioral perception in relation to the variable and efficiency variable involved. There are endogenous variables dependent variables with whom are prescribed in variables, so they are called endogenous variables. Exogenous variables are those which are prescribed outside of the model. A variable weather is endogenous or exogenous it depends on the purpose of the model.
3. Secondly, data is collected for both endogenous and exogenous variables. Exogenous variable are like tax rates, any supply etc. The next step after the data is collecting and developing the model is to guess the model through the appropriate method, usually two phase of at least class method is used to predict exogenous variable values, finally, the model is solved in terms of exogenous variable for each endogenous variable. There the objective value is calculated by putting the values of exotic variants in the equation and predicting.